ABSTRACT
As NASA prepares for crewed lunar missions over the next several years, plans are also underway to journey farther into deep space. Deep space exploration will require a paradigm shift in astronaut medical support toward progressively earth-independent medical operations (EIMO). The Exploration Medical Capability (ExMC) element of NASA's Human Research Program (HRP) is investigating the feasibility and value of advanced capabilities to promote and enhance EIMO. Currently, astronauts rely on real-time communication with ground-based medical providers. However, as the distance from Earth increases, so do communication delays and disruptions. Moreover, resupply and evacuation will become increasingly complex, if not impossible, on deep space missions. In contrast to today's missions in low earth orbit (LEO), where most medical expertise and decision-making are ground-based, an exploration crew will need to autonomously detect, diagnose, treat, and prevent medical events. Due to the sheer amount of pre-mission training required to execute a human spaceflight mission, there is often little time to devote exclusively to medical training. One potential solution is to augment the long duration exploration crew's knowledge, skills, and abilities with a clinical decision support system (CDSS). An analysis of preliminary data indicates the potential benefits of a CDSS to mission outcomes when augmenting cognitive and procedural performance of an autonomous crew performing medical operations, and we provide an illustrative scenario of how such a CDSS might function.
ABSTRACT
The aim of this project is to extend accurate and patient-specific treatment planning to new treatment modalities, such as molecular targeted radiation therapy, incorporating previously crafted and proven Monte Carlo and deterministic computation methods. A flexible software environment is being created that allows planning radiation treatment for these new modalities and combining different forms of radiation treatment with consideration of biological effects. The system uses common input interfaces, medical image sets for definition of patient geometry and dose reporting protocols. Previously, the Idaho National Engineering and Environmental Laboratory (INEEL), Montana State University (MSU) and Lawrence Livermore National Laboratory (LLNL) had accrued experience in the development and application of Monte Carlo based, three-dimensional, computational dosimetry and treatment planning tools for radiotherapy in several specialized areas. In particular, INEEL and MSU have developed computational dosimetry systems for neutron radiotherapy and neutron capture therapy, while LLNL has developed the PEREGRINE computational system for external beam photon-electron therapy. Building on that experience, the INEEL and MSU are developing the MINERVA (modality inclusive environment for radiotherapeutic variable analysis) software system as a general framework for computational dosimetry and treatment planning for a variety of emerging forms of radiotherapy. In collaboration with this development, LLNL has extended its PEREGRINE code to accommodate internal sources for molecular targeted radiotherapy (MTR), and has interfaced it with the plugin architecture of MINERVA. Results from the extended PEREGRINE code have been compared to published data from other codes, and found to be in general agreement (EGS4-2%, MCNP-10%) (Descalle et al 2003 Cancer Biother. Radiopharm. 18 71-9). The code is currently being benchmarked against experimental data. The interpatient variability of the drug pharmacokinetics in MTR can only be properly accounted for by image-based, patient-specific treatment planning, as has been common in external beam radiation therapy for many years. MINERVA offers 3D Monte Carlo-based MTR treatment planning as its first integrated operational capability. The new MINERVA system will ultimately incorporate capabilities for a comprehensive list of radiation therapies. In progress are modules for external beam photon-electron therapy and boron neutron capture therapy (BNCT). Brachytherapy and proton therapy are planned. Through the open application programming interface (API), other groups can add their own modules and share them with the community.
